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Stochastic Modelling – Boon or Bane for Insurance Industry Capital Regulation?

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Author Info
Oliver B&aauml;te (McKinsey & Company, Inc., Magnusstraße 11, 50672 Köln, Germany.)
Philipp von Plato (McKinsey & Company, Inc., Magnusstraße 11, 50672 Köln, Germany.)
Günther Thallinger () (McKinsey & Company, Inc., Magnusstraße 11, 50672 Köln, Germany.)
Abstract

Regulation of the financial industry should pursue three key objectives: consumer protection, market stability, and competitive efficiency. This article discusses core elements of a capital regime that could be used to develop regulation that meets these objectives while fostering an industry-wide enhancement of risk management. The authors argue that a pre-commitment approach can have considerable advantages over regulation based on (stochastic) risk models, as the latter can have adverse effects, especially on market stability and competitive efficiency, while consumer protection would have to be supplemented by additional requirements (such as scenario tests) in any case. Academic studies on capital regulation based on stochastic models have focused more on banking and less on insurance, while work by insurance practitioners has concentrated on the implications for management. The authors, therefore, wish to contribute to a more fundamental discussion of the design of capital and risk management regulation of the insurance industry. The Geneva Papers (2006) 31, 57–82. doi:10.1057/palgrave.gpp.2510071

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Article provided by Palgrave Macmillan Journals in its journal The Geneva Papers on Risk and Insurance Issues and Practice.

Volume (Year): 31 (2006)
Issue (Month): 1 (January)
Pages: 57-82
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Handle: RePEc:pal:gpprii:v:31:y:2006:i:1:p:57-82

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